Sr. Marketing Content Strategist, AI Visibility
CockroachDBNew York, NYPosted 14 April 2026
Job Description
Category-defining tech. Career-defining work.
Lots of tech companies disrupt. But, many fail when they try to scale. We're different. CockroachDB makes it easier for companies to build and scale apps. This is how and why we're helping some of the most innovative companies on the planet. We tackle problems head-on and focus on solutions that create lasting impact.
Because when our customers win, we all win.
The Role
We're hiring a Sr. Marketing Content Strategist to help evolve and scale our content strategy for an AI-first, answer-driven landscape. This role sits within the Corporate Marketing function and reports directly to the Head of Corporate Marketing. You'll play a foundational role in shaping how Cockroach Labs structures, governs, and operationalizes content across the organization.
This is not primarily a writing role. It's about building the systems, governance, and cross-functional processes that ensure our content is structured, discoverable, reusable, and optimized for both humans and LLMs — sitting at the intersection of content strategy, SEO/AEO, marketing operations, product marketing, and analytics. Your work will ensure Cockroach Labs' content is built for AI visibility, search discoverability, and measurable business impact by default, not as an afterthought.
You Will
Build Scalable Content Systems
Design and implement content frameworks aligned to search engines, answer engines, and AI agents
Define structured content models including taxonomy, metadata, schema, and modular architecture
Partner with Web and Digital teams to ensure technical implementation supports discoverability and reuse
Establish governance standards that enable content reuse across channels, regions, and formats
Lead Answer Engine Optimization (AEO)
Translate AI search and AEO trends into actionable content architecture
Develop guidelines for machine-readable, structured, and citation-friendly content
Optimize content for LLM retrieval, featured snippets, and zero-click experiences
Build feedback loops to measure and improve visibility across AI-driven surfaces
Design Content Operations
Create scalable intake, production, and publishing workflows
Define RACI models across Product Marketing, Brand, Demand Gen, and Comms
Standardize briefs, templates, QA processes, and performance reporting
Evaluate and evolve the content tech stack (CMS, DAM, AI tools, SEO tools)
Orchestrate Cross-Functional Alignment
Align stakeholders across Marketing, Product, and Sales around shared frameworks
Train internal teams on structured content best practices
Serve as the connective layer between strategy and execution
Measure Optimize
Define KPIs for discoverability, answer visibility, and content reuse efficiency
Build dashboards that connect content performance to pipeline and authority
Identify operational bottlenecks and continuously improve throughput and quality
The Expectations
In your first 30 days, you'll immerse yourself in our content ecosystem, meet key stakeholders across Marketing and Product, and audit our current content systems and workflows
By 60 days, you'll define a scalable content architecture framework and begin piloting structured models with priority team.
By 90 days, you'll implement governance standards, launch measurable AEO initiatives, and establish performance dashboards that tie content structure to business impact
You Have
6-8+ years of experience in content strategy, SEO, content operations, or marketing operations
Deep understanding of technical SEO, and evolving search behavior
Background in B2B or technical marketing
Experience designing scalable workflows across multi-team, fast-moving environments
A systems-thinking mindset — you see content as an asset, not an output
Proven ability to influence without authority and drive alignment across cross-functional teams
Comfort operating in environments where AI is reshaping discovery and engagement
Nice to Have
Experience optimizing ... (truncated, view full listing at source)
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